The Architecture of Complex Deals

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Risk is not a self-licking lollipop. Nor is risk a beautiful and delicate flower to be tended and admired on its own. Risk is part of a system (Assurance) and that system has a point and the point is to reduce cost and time growth; both now and in the future.

Pull-Through

It does this in two ways: (i) operational pull-through, and (ii) commercial pull-through. Where operational pull-through reduces cost and time overrun now, commercial pull through reduces cost and time overrun (often the same) in the future by breaking the causal chain of a potential claim as well as by reducing future liability by addressing specific areas of causation. Traditional Risk Management addresses operational pull-through. The goal is to assess what might go wrong on a project in the immediate future. The structure of the deal and any inherent soft-spots within it are rarely given thought. Commercial pull-through is just as, if not more, important. Commercial pull-through will support or defend claims (either extension-of-time or cost) and it will help resolve further issues of liability.

“The financial risk is hardly ever worth taking. I have just seen a £5m job ending up with a £12m claim. A lot of clients are still not prepared to spend the money up front to get the contract, the budget and the contingency right. I would say you can end up spending around 10 times as much resolving a dispute compared to what you would have needed to put in at the start to avoid it becoming an issue.”

Gary Kitt, head of contract solutions in the UK for EC Harris.

The linchpin for both is causation and the key to proving causation is through causal chains.

Causal Chains

Figure 1 below outlines a causal chain for a fictitious business problem. In this case, low quality steel is likely to affect the build of a steel frame on a construction site. The Contractor, warranting the workmanship of the building, they will be liable for defects in the future. Additionally, they have operational liability now and will likely incur some cost growth through re-work. ‘What is the cause?’ is an ontological question. ‘How can the business reduce their liability and current costs?’ is a business question. In the example below the Supplier’s liability is counterweighted by an equally damaging causal chain derived from the Contractor’s poor welding. Without the ability to define and delineate these causal chains – and therefore limit libility – the Contractor will have, prima facie, extensive liability from poor workmanship.

In exploring the context of our example somewhat more, we begin to understand that although the lower capability of the workforce was compounded by a low supervision ratio, the welds themselves were of a sufficient standard to warrant their quality. A poor understanding and examination of the causal chain would not have held out such analysis. A poor understanding has the lawyers and commercial team clutching at straws rather than aiming to rebut or settle the claim.

Figure 1 – A causal chain from a Construction Company example.

Causation: Assumptions v Weaknesses

The primary problem with causal chains in the poor understanding of causation itself. In the aforementioned example at Figure 1 many Risk Managers would misassociate the possibility of the framework buckling with the assumptions and technical trends further upstream. None of them, however, on their own are either sufficient or necessary to cause the buckling of the frame. Causation can have multiple factors but only so many that are sufficient and necessary to give rise to the risk. In this case, some of our causes can be demarcated into a different causal chain altogether. If placed together, therefore, would confuse the commercial negotiating leverage that such risk analysis was able to provide.

Counter-Factual Argument

Be careful of counter-factual arguments, i.e. the “but for” or sine qua non analysis of causation. Scholars of causation theory, such as David Lewis, were deeply sceptical of counterfactuals. For example, were a cat to jump out of a window after I had unlatched it, prove causation? No but under a sine qua non my guilt would be highlighted.

Risks: Events v Transitions

One should never think of a business risk as an event. This may be heresy to some but unless you can easily distinguish between the causation events, risk events and impact events then you should seek to differentiate the language used to define them. To try and conceptually isolate individual events is like trying to spot the offending domino. They all played a part. However, by having a language and methodology to differentiate causal elements and causal chains one has the ability to reduce duplication and redundancy in quantitative risk simulations. For instance, when deconstructing problems we talk about ‘structural weaknesses’ and not causal events. Such language helps us delineate between causal events rather than redefine a taxonomy of risk.

Risk statements are often the hardest to differentiate. One can understand causal events (although pinning them in time can be difficult without the right language) but structuring a risk statement itself can be conceptually difficult. A risk, after all, is artificial. Instinctively, we know cause-and-effect but risk is far less intuitive.

Conceptualising risk as yet another event in the causal chain opens risk up for too much confusion. What is needed is a way to encapsulate, in a risk statement, the impact to the business of a causal chain. One way to do this is through transition statements. Viewing risk as a potentially harmful state transition is a useful way to construct effective risk statements. For instance, the risk of falling off my chair at work is not in hurting my back or even breaking the chair. It is that I will transition from earning to not earning. Wording risk as such allows us to articulate the causal chain without contaminating it with an artificial risk statement, i.e. the risk statement is the conceptualisation of a discrete part of the causal chain.

Impacts: Impacts v Effects

It is important to distinguish between types of impacts in causal chains, after all, not all impacts are relevant or useful but can be included by naysayers and contrarians to obfuscate the effect of a risk and thereby avoid being delegated work. The impact that is relevant in risk is the direct causal impact. Impacts felt further downstream are important and may be relevant but not to an accountant or lawyer. Downstream impacts may be distinguished as ‘effects’ and therefore only of indirect causal significance.

In summ, there is not commercial pull-through without precise causal chains. Claims can be developed and leverage gained without them but always imprecise and far more costly to generate. If Risk is ever to be a sophisticated, value-adding practice in the business then it must show commercial pull-through and to do that it must start with supporting the development and analysis of causal chains.